The Kolachalama Group seeks to create "methods to fit the science and not make science fit the methods."

Specifically, they are interested in the following clinically relevant questions:
1. Neurodegeneration—How can we develop software frameworks that can assist dementia screening in various real-world settings?
2. Digital pathology—How can we build clinical-grade software tools to complement the clinical workflow?

The team is also interested in the following computationally relevant frameworks:
1. Domain generalization—Development of deep neural networks that can generalize well across multiple data cohorts.
2. Representation learning—Construction of efficient neural models on high-resolution data to process local and contextual information.

In this video members of the Kolachalama Group introduce their work using machine learning to diagnose Alzheimer's.